According to housing investment models, house prices and replacement cost should have an equilibrating relationship. Previous empirical work - mainly based on aggregate-level data - has found only little evidence of such a relationship. By using a unique data set, covering transactions of single-family houses over a 25 years period, we establish strong support for the relationship at the micro level. In the time series context, we find that new house prices and replacement cost align quickly after a shock. In the cross-sectional context, we find prices of old houses and replacement cost are closely related once building depreciation has been taken into account. As to be expected from these results, replacement cost information also proves to be useful for the prediction of future house prices.